[R-sig-eco] species richness, GLM and negative values

[Kay Cichini]

..or we could include 'Plot' as random variable?

library(lme4)
mod <- glmm(DS ~ Time + 1|Plot)

Yours,
Kay


Von meinem Smartphone gesendet

Bob O'Hara <bohara at senckenberg.de> schrieb:

>On 10/29/2014 04:27 PM, Ludovico Frate wrote:
>> Dear all,I'am trying to fit a very simple linear model. I am analyzing the differences in the number of species (DS) found in several permanent plots in two year of observations.
>>   Firstly, I have calculated the differences per plot (i.e. number of species in Plot 1 in Time A - number of species in Plot 1 in Time B and so on for all the plots).Secondly, those differences were tested for deviation from zero by means of a linear model
>> M2<-lm(DC~1, data = gransasso)summary(M2)E2<-residuals(M2)qqnorm(E2, pch = 19, col = "blue"); qqline(E2, col = "red")
>> The qqnorm has shown that residuals were not normally distributed, thus I need to use a GLM. However GLM (poisson family) does not work with negative values (DS has negative values).I've tried to add a constant value to these differences (i.e. +100) but the result is misleading  since I am testing for deviation from zero.
>> Do you have any suggestions?
>> Regards,Ludovico
>Use the Poisson to model the number of species in each sample, so use 
>data like this:
>
>Plot  Time   DS
>1      A         4
>1      B         7
>2      A         0
>2      B         1
>3      A         23
>3      B         7
>...
>
>Then you fit the model
>
>Mgood <- glm(DS ~ Plot + Time, family=poisson())
>
>where Plot and Time are factors (use Plot <- factor(Plot), for example, 
>if you need to).
>
>You're interested in the Time effect, which is the average difference 
>between the numbers of species in the plots in the different times. The 
>Plot effect controls for different plots having different numbers of 
>species overall. If you look at summary(Mgood), the Time effect is the 
>log of the ratio of the species richnesses in times A and B. It will be 
>written as TimeB, which means it's log(E.B/E.A) (where E.A and E.B are 
>the expected species richnesses at times A and B). So, for example, an 
>estimate of 0.4 would mean that at Time B there are exp(0.4)=1.49 times 
>more species at time B than time A.
>
>Bob
>
>
>>                                                                                                                               
>> Ludovico
>> Frate
>>
>> PhD student (University of Molise - Italy)
>> Environmetrics Lab
>> http://www.distat.unimol.it/STAT/environmetrica/organico/collaboratori/ludovico-frate-1
>> Department of Biosciences and Territory - DiBT
>> Universit� del Molise.
>> Contrada Fonte
>> Lappone,
>> 86090 -  Pesche (IS)
>> ITALIA.
>> Cel: ++39
>> 3333767557
>> Fax: ++39 (0874) 404123
>> E-mail ludovico.frate at unimol.it
>> ludovicofrate at hotmail.it
>>   		 	   		
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>>
>>
>>
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>
>
>-- 
>Bob O'Hara
>
>Biodiversity and Climate Research Centre
>Senckenberganlage 25
>D-60325 Frankfurt am Main,
>Germany
>
>Tel: +49 69 7542 1863
>Mobile: +49 1515 888 5440
>WWW:   http://www.bik-f.de/root/index.php?page_id=219
>Blog: http://blogs.nature.com/boboh
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>
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